AI Research

Agentic AI: MCP Protocol, Tool Calling Standardization, and AI Workflow Automation in 2025

Agentic AI: MCP Protocol, Tool Calling Standardization, and AI Workflow Automation in 2025

A major 2024–2025 AI trend is Agentic AI scaling into production — AI evolving from single-turn conversational assistants toward autonomous workers ex

未知作者 未知作者 2026-06-07
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AI Content Detection and Digital Watermarking: Authenticating AI-Generated Text and Images

AI Content Detection and Digital Watermarking: Authenticating AI-Generated Text and Images

As AI-generated content quality rises rapidly, "is this AI-written/generated?" has become a high-frequency question in education, journalism, and law.

未知作者 未知作者 2026-06-05
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LLM Evaluation Benchmarks Explained: MMLU, HumanEval, HELM, and the Benchmark Saturation Problem

LLM Evaluation Benchmarks Explained: MMLU, HumanEval, HELM, and the Benchmark Saturation Problem

MMLU, HumanEval, and HELM are the most-cited LLM evaluation benchmarks. But as model scores on these benchmarks rise, "benchmark saturation" and data

未知作者 未知作者 2026-06-03
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Federated Learning and Privacy-Preserving ML: Training AI Without Sharing Raw Data

Federated Learning and Privacy-Preserving ML: Training AI Without Sharing Raw Data

Federated Learning trains machine learning models while data stays local — participants share only model gradients, not raw data, and collaboratively

未知作者 未知作者 2026-06-02
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AI Search Engines: Perplexity, SearchGPT, and the Paradigm Difference from Traditional Search

AI Search Engines: Perplexity, SearchGPT, and the Paradigm Difference from Traditional Search

AI-powered search combines LLM language understanding with real-time web retrieval, returning synthesized answers rather than link lists. Perplexity A

未知作者 未知作者 2026-05-31
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AI Code Generation: GitHub Copilot, Cursor, and Devin’s Capability Boundaries

AI Code Generation: GitHub Copilot, Cursor, and Devin’s Capability Boundaries

AI code generation tools have evolved from autocomplete assistance to completing full functional modules independently. Copilot, Cursor, and Devin rep

未知作者 未知作者 2026-05-29
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Text-to-Video AI: Sora, Runway Gen-3, and Kling’s Technology and Creative Applications

Text-to-Video AI: Sora, Runway Gen-3, and Kling’s Technology and Creative Applications

OpenAI's Sora (2024) demonstrated AI generating coherent 60-second high-quality videos from text prompts, shocking the film and creative industry. Vid

未知作者 未知作者 2026-05-27
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LLM Inference Optimization: Quantization, Speculative Decoding, and KV Cache Engineering

LLM Inference Optimization: Quantization, Speculative Decoding, and KV Cache Engineering

Training a large model is a one-time cost; serving hundreds of millions of users accumulates inference costs continuously. Quantization, speculative d

未知作者 未知作者 2026-05-26
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Self-Supervised and Contrastive Learning: BERT, CLIP, and the Unlabeled Data Revolution in Representation Learning

Self-Supervised and Contrastive Learning: BERT, CLIP, and the Unlabeled Data Revolution in Representation Learning

Supervised learning depends on large labeled datasets. Self-supervised learning constructs supervision signals from data itself, learning feature repr

未知作者 未知作者 2025-04-05
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Reinforcement Learning: From Board Games to Real Robots — AlphaGo, AlphaStar, and Robot Manipulation

Reinforcement Learning: From Board Games to Real Robots — AlphaGo, AlphaStar, and Robot Manipulation

Reinforcement Learning trains AI through environment interaction to maximize cumulative reward — fundamentally different from supervised learning's la

未知作者 未知作者 2025-03-31
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